Automated LLM Testing: Why Evaluation Harnesses Are the Unit Tests of AI

Evaluation harnesses transform LLM testing from subjective 'vibes checks' into reproducible, measurable processes—enabling teams to catch regressions in CI, compare model versions meaningfully, and defend design decisions with data. By decoupling the model from the benchmark, these tools let organizations curate benchmarks that actually matter for their use cases, turning ad-hoc testing into a scalable, CI-integrated practice that treats model evaluation like software engineers treat unit tests.